Parallel-serial hybrid electrical vehicle control strategy based on dynamic programming algorithm

According to the configuration of a certain parallel-serial hybrid electric vehicle (PSHEV), a mathematical model was built for the vehicle control. An optimization function was proposed taking the engine fuel consumption minimization and the state-of-charge (SOC) idealization in the whole operation cycle as the targets. A dynamically limited SOC region model was built. A global search algorithm was designed for the dynamic programming. The shifting logic was also optimized. The PSHEV control strategy based on the power-tracking algorithm, that based on the dynamic programming and that based on the improved power-tracking algorithm were compared each other and the results show that the dynamic programming algorithm can be regarded as the reference of judgement for other control strategies, and can be used as to improve the control effectiveness of power-tracking control strategies.